Two-dimensional　(2D)　materials　based　artificial　synapses　are　important　building　blocks　for　the　brain-inspired　computing　systems　that　are　promising　in　handling　large　amounts　of　informational　data　with　high　energy-efficiency　in　the　future.　However,　2D　devices　usually　rely　on　deposited　or　transferred　insulators　as　the　dielectric　layer,　resulting　in　various　challenges　in　device　compatibility　and　fabrication　complexity.　Here,　we　demonstrate　a　controllable　and　reliable　oxidation　process　to　turn　2D　semiconductor　HfS2　into　native　oxide,　HfOx,　which　shows　good　insulating　property　and　clean　interface　with　HfS2.　We　then　incorporate　the　HfOx/HfS2　heterostructure　into　a　flash　memory　device,　achieving　a　high　on/off　current　ratio　of　similar　to　10(5),　a　large　memory　window　over　60　V,　good　endurance,　and　a　long　retention　time　over　similar　to　10(3)　seconds.　In　particular,　the　memory　device　can　work　as　an　artificial　synapse　to　emulate　basic　synaptic　functions　and　feature　good　linearity　and　symmetry　in　conductance　change　during　long-term　potentiation/depression　processes.　A　simulated　artificial　neural　network　based　on　our　synaptic　device　achieves　a　high　accuracy　of　similar　to　88%　in　MNIST　pattern　recognition.　Our　work　provides　a　simple　and　effective　approach　for　integrating　high-k　dielectrics　into　2D　material-based　memory　and　synaptic　devices.